Control Neuroborroso en Red. Aplicación al Proceso de Taladrado de Alto Rendimiento
[EN] The neurofuzzy system known as Adaptive Network-based Fuzzy Inference System (ANFIS), is a pioneering work, as well as the simplest computationally and the most viable for real-time applications. This work is focused on designing and implementing a neurofuzzy control system of a high-performanc...
| Autores: | ; |
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| Tipo de documento: | Artículo |
| Fecha de publicación: | 2009 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Lenguaje: | Español |
| OAI Identifier: | oai:riunet.upv.es:10251/145383 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/145383 |
| Nivel de acceso: | Acceso abierto |
| Palabra clave: | Neurofuzzy systems Internal model control Networked control High-performance drilling process Sistemas neuroborrosos Control por modelo interno Control en red Taladrado de alto rendimiento |
| Sumario: | [EN] The neurofuzzy system known as Adaptive Network-based Fuzzy Inference System (ANFIS), is a pioneering work, as well as the simplest computationally and the most viable for real-time applications. This work is focused on designing and implementing a neurofuzzy control system of a high-performance drilling process through a Profibus network. The internal model control (IMC) paradigm accomplishes this goal by using direct and inverse process models for designing the control system. From the technical point of view, the aim is to maximize both the material removal rate and useful tool life. The results obtained are significant both in simulation as well as the real time application which are also verified by several performance indices. |
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